The presence of multiple health conditions complicates Health Related Quality of Life (HRQoL) impact estimates for specific conditions used in cost-effectiveness analyses. The overall goal of this project is to find the best method to estimate the impact of a single health condition when multiple conditions are present. Previous research focused on modeling summary health scores; our research will attempt to improve summary health score estimates by modeling the individual questions which are used to calculate these scores. Specifically, we will (1) develop and validate a question-level model of co-occurring conditions in HRQoL measures, (2) evaluate this question-level model against the best summary score model (3) construct a nationally representative catalog of HRQoL impact for 117 chronic conditions, and (4) demonstrate the use of the catalog to remove the effect of co-occurring conditions from a new sample. We will use a large Medicare database to develop, validate, and evaluate our model. We will use respondents aged 18 and over from the Medical Expenditures Panel Survey, a large nationally representative survey, to catalog the impact of 117 chronic conditions. These 2 datasets include a number of AHRQ-defined priority populations such as women, racial and ethnic minorities, low income, rural, and inner city individuals. We will use a clinic-based sample of heart failure patients to demonstrate use of our methods in smaller samples. We will predict question responses with a proportional odds model that uses age, sex, and health conditions as predictors. The proposed research will provide valuable methods for health measurement which informs health policy. [unreadable] [unreadable] [unreadable]